INTERNATIONAL DISTINGUISHED INNOVATION AWARD
I’m Naresh Dulam, currently serving as Vice President and Senior Manager of Data Engineering at JP Morgan Chase & Co. in the United States. My journey in technology spans over a decade, beginning with a Bachelor of Technology in Computer Science and Engineering from JNTU University and evolving into a career deeply rooted in data engineering, cloud platforms, and AI-driven innovation. I’ve had the privilege of working across some of the world’s most influential organizations, leading transformative initiatives that modernize legacy systems, accelerate insights, and enable large-scale data accessibility. At JP Morgan Chase, I’ve been focused on building next-generation hybrid data platforms, driving forward the firm’s vision of scalable, secure, and efficient data operations. One of my most impactful contributions has been the design and implementation of the JADE Analytics Platform—a hybrid cloud ingestion framework that enables seamless onboarding of diverse data sources. It now supports over 45 teams, offering robust scalability and consistency across business units. Another major highlight was the creation of the Risk Insights platform, powered by GenAI, which revolutionized how trust documents are analyzed for risk and compliance. These innovations have not only enhanced performance and governance but also contributed to saving over $100 million in resources for the firm. Throughout my career, I’ve held several strategic roles, including positions at HCSC, AT&T, Bank of America, and T-Mobile, where I worked on large-scale big data engineering initiatives. My early career began in India at Oracle and Infor, where I developed a strong foundation in application engineering and data systems. These experiences collectively helped shape my ability to work across cloud, on-premises, and hybrid environments with a sharp focus on performance, security, and cost optimization. My approach has always been driven by creating frameworks that are reusable, scalable, and aligned with modern data architecture principles. I’ve developed several key tools, such as the Spark Transformation Framework, which abstracts complexity from big data processing using metadata and SQL-based logic. My MDM Authored Attributes system supports dynamic data ingestion into Hadoop ecosystems, while my Python Data Virtualization API empowers data analysts with simplified libraries for advanced analytics. These tools have not only streamlined development but also accelerated the adoption of AI/ML across departments. I’m proud to be a certified AWS Solutions Architect and Data Analytics Specialist, and I also hold Kubernetes certifications including CKAD, CKA, and CKS, along with Snowflake’s SnowPro Core and Azure’s AZ-900. These certifications represent my continuous pursuit of learning and my drive to stay at the forefront of emerging technologies. Being honored with the “Best Data AIML Leader” award is deeply meaningful to me. It’s a reflection not just of my individual efforts, but of the collaboration and vision shared with incredible teams over the years. I’m grateful to have had the opportunity to transition complex legacy systems to agile, cloud-first architectures—work that has led to improved analytics capabilities and measurable business growth. One such milestone was delivering advanced analytics sandbox solutions during the COVID-19 pandemic, which enabled real-time insights and helped inform crucial business decisions. I extend my sincere gratitude to my colleagues, mentors, and leadership at JP Morgan Chase & Co. for their trust and support, and to my family for their unwavering encouragement. I am also thankful for the recognition by esteemed organizations such as ISSN, Titan, and the Asian awards bodies, which have acknowledged my contributions to the global data and AI ecosystem. Looking ahead, my mission is to continue shaping data ecosystems that are not only technically sound but also inclusive, ethical, and accessible. I believe that true innovation lies in democratizing data and enabling every business unit to act with intelligence and agility. With every new challenge, I aim to build with purpose, lead with empathy, and contribute meaningfully to the future of data engineering.